Enterprise AI is moving beyond copilots and chatbots into fully autonomous agents—and cybersecurity vendors are racing to keep up. Straiker believes the next major security challenge isn’t protecting people from AI, but protecting organizations from what AI agents can unintentionally—or maliciously—do.
The startup announced a $64 million Series A funding round, bringing its total funding to $85 million. The investment was led by Marathon Management Partners, Citi Ventures, Illuminate Financial, and Workday Ventures, with continued participation from Bain Capital Ventures and Lightspeed. As part of the investment, Marathon founding partner Gokul Rajaram joins Straiker’s board of directors.
The fresh capital will be used to accelerate product development, expand the company’s AI threat research arm, STAR Labs, and support international growth as demand for AI security accelerates.
AI Agents Are Becoming Enterprise Employees—With Enterprise Risks
Generative AI has quickly evolved from productivity assistants into autonomous software agents capable of making decisions, interacting with applications, executing workflows, and accessing sensitive enterprise systems with minimal human oversight.
Industry analysts expect that trend to accelerate dramatically. IDC projects enterprises will deploy more than one billion AI agents by 2029, representing roughly a 40-fold increase compared to 2025. As organizations increasingly automate customer service, software development, finance, HR operations, and internal workflows, securing these autonomous systems is becoming a boardroom concern rather than simply an IT project.
Unlike traditional software, AI agents continuously reason, adapt, and make decisions in real time. That flexibility delivers significant productivity gains but also introduces entirely new attack surfaces that conventional cybersecurity tools weren’t designed to monitor.
Recent incidents have highlighted those risks. Attackers have demonstrated how prompt injection, indirect manipulation, and agent misuse can bypass traditional security controls without exploiting software vulnerabilities or stealing user credentials.
Straiker Wants to Become the Security Layer for AI Agents
Straiker is positioning itself as an “agentic security” platform built specifically for organizations deploying autonomous AI systems.
Rather than focusing solely on model security or application protection, the platform aims to provide visibility into every AI agent operating across an enterprise, understand what systems those agents can access, evaluate their behavior, and identify emerging security risks before they become incidents.
The company’s platform combines three primary capabilities:
- Enterprise-wide discovery of AI agents and their permissions
- Pre-deployment adversarial testing to identify vulnerabilities before rollout
- Runtime monitoring and threat prevention to detect and stop attacks against live AI agents
What differentiates the platform is a shared intelligence layer that continuously feeds insights between testing and production environments. Threats observed in real-world deployments strengthen future security testing, while vulnerabilities discovered during testing improve runtime detection capabilities.
According to Straiker, that feedback loop allows its security engine to evolve alongside increasingly sophisticated AI systems and attack techniques.
“Our uniqueness comes from pairing the industry’s most comprehensive agentic exploit dataset with an AI-native security engine purpose-built for autonomous threats,” said Co-Founder and CTO Sreenath Kurupati.
STAR Labs Highlights the Risks of Autonomous AI
Supporting Straiker’s platform is STAR Labs, the company’s dedicated AI threat research division, which conducts adversarial testing against AI systems.
Its recent research paints a concerning picture of the current AI security landscape.
According to the company, 36% of successful attacks targeting AI coding agents resulted in remote code execution, while 91% of successful attacks against productivity agents led to silent data exfiltration—all without malware deployment or compromised credentials.
Those findings underscore a growing realization across cybersecurity teams: protecting AI agents requires fundamentally different approaches than protecting traditional applications.
Instead of defending fixed software code, organizations must monitor systems capable of dynamically interpreting instructions, interacting with APIs, and making autonomous decisions that can change based on context.
Built by Security Veterans
Straiker’s leadership combines experience in both enterprise cybersecurity and artificial intelligence.
CEO Ankur Shah previously led the growth of Prisma Cloud at Palo Alto Networks, while CTO Sreenath Kurupati led AI and security research at Akamai following its acquisition of Cyberfend, the fraud detection company he founded.
That combination has helped the startup gain traction with both frontier AI labs and Fortune 500 organizations since launching in 2025.
The company says annualized revenue has increased more than 15 times within its first year, reflecting rapidly growing enterprise demand for AI-native security solutions.
“Demand is outpacing anything we forecast,” Shah said, adding that the new funding will accelerate product innovation, expand STAR Labs, and support the company’s international expansion plans.
Why Investors Are Betting on Agentic Security
The funding round reflects growing investor confidence that AI security will become one of enterprise software’s fastest-growing categories over the next several years.
While many cybersecurity vendors have added AI features to existing platforms, a new generation of startups—including Straiker—is building products specifically around autonomous AI systems rather than adapting legacy security architectures.
Competition in the emerging AI security market continues to intensify as enterprises look for ways to safely deploy increasingly capable AI agents. Vendors such as Protect AI, HiddenLayer, Lakera, Robust Intelligence (now part of Cisco), and Palo Alto Networks are all investing heavily in AI model protection, runtime monitoring, and governance capabilities.
Straiker’s focus on securing autonomous AI agents represents a distinct niche within that broader market—one that could become increasingly important as enterprises shift from AI assistants to AI systems capable of independently executing business processes.
For HR leaders, CIOs, CISOs, and enterprise technology teams, the message is becoming clear: as AI agents gain access to payroll systems, HR platforms, customer records, financial applications, and software development environments, securing those digital workers may soon become as important as securing human employees.
If AI agents truly become the fastest-growing workforce in enterprise history, the market for protecting them is likely to grow just as quickly.
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